June 2020 arXiv papers — page 32

David Joseph, Adam Callison, Cong Ling, Florian Mintert

Quantum computers are expected to break today's public key cryptography within a few decades. New cryptosystems are being designed and standardised for the post-quantum era, and a significant proportion of these rely on the hardness of problems like the Shortest Vector Problem to a quantum adversary. In this paper we describe two variants of a quantum Is

Soulaimane Berkane, Abdelhamid Tayebi, Simone de Marco

This paper deals with the problem of full state estimation for vehicles navigating in a three dimensional space. We assume that the vehicle is equipped with an Inertial Measurement Unit (IMU) providing body-frame measurements of the angular velocity, the specific force, and the Earth's magnetic field. Moreover, we consider available sensors that provide

V. A. Mikhailov, N. V. Troshkin

In this paper we investigate non-Markovian evolution of a two-level system (qubit) in a bosonic bath under influence of an external classical fluctuating environment. The interaction with the bath has the Lorentzian spectral density, and the fluctuating environment (stochastic field) is represented by a set of Ornstein-Uhlenbeck processes. Each of the subenv

Isaac Goldbring, Srivatsav Kunnawalkam Elayavalli, Yash Lodha

We introduce and study Polish topologies on various spaces of countable enumerated groups, where an enumerated group is simply a group whose underlying set is the set of natural numbers. Using elementary tools and well known examples from combinatorial group theory, combined with the Baire category theorem, we obtain a plethora of results demonstrating that

T. -S. Lin, J. A. Dijksman, L. Kondic

We explore flow of a completely wetting fluid in a funnel, with particular focus on contact line instabilities at the fluid front. While the flow in a funnel may be related to a number of other flow configurations as limiting cases, understanding its stability is complicated due to the presence of additional azimuthal curvature, as well as due to convergent

Steve Alpern, Bo Chen

We consider an odd-sized "jury", which votes sequentially between two states of Nature (say A and B, or Innocent and Guilty) with the majority opinion determining the verdict. Jurors have private information in the form of a signal in [-1,+1], with higher signals indicating A more likely. Each juror has an ability in [0,1], which is proportional to t

Sergey Bravyi, Sarah Sheldon, Abhinav Kandala, David C. Mckay

Reducing measurement errors in multi-qubit quantum devices is critical for performing any quantum algorithm. Here we show how to mitigate measurement errors by a classical post-processing of the measured outcomes. Our techniques apply to any experiment where measurement outcomes are used for computing expected values of observables. Two error mitigation sche

Huiying Li, Shawn Shan, Emily Wenger, Jiayun Zhang

Deep learning systems are known to be vulnerable to adversarial examples. In particular, query-based black-box attacks do not require knowledge of the deep learning model, but can compute adversarial examples over the network by submitting queries and inspecting returns. Recent work largely improves the efficiency of those attacks, demonstrating their practi

Tefjol Pllaha, Narayanan Rengaswamy, Olav Tirkkonen, Robert Calderbank

The teleportation model of quantum computation introduced by Gottesman and Chuang (1999) motivated the development of the Clifford hierarchy. Despite its intrinsic value for quantum computing, the widespread use of magic state distillation, which is closely related to this model, emphasizes the importance of comprehending the hierarchy. There is currently a

Marcos L. W. Basso, Jonas Maziero

One of the fundamental differences between classical and quantum mechanics is in the ways correlations can be distributed among the many parties that compose a system. While classical correlations can be shared among many subsystems, in general quantum correlations cannot be freely shared. This unique property is known as monogamy of quantum correlations. In

Gumaro Rendon, Luka Leskovec, Stefan Meinel, John Negele

We present a lattice-QCD determination of the elastic isospin-$1/2$ $S$-wave and $P$-wave $Kπ$ scattering amplitudes as a function of the center-of-mass energy using Lüscher's method. We perform global fits of $K$-matrix parametrizations to the finite-volume energy spectra for all irreducible representations with total momenta up to $\sqrt{3}\frac{2π}{L}

Jesse Mu, Jacob Andreas

We describe a procedure for explaining neurons in deep representations by identifying compositional logical concepts that closely approximate neuron behavior. Compared to prior work that uses atomic labels as explanations, analyzing neurons compositionally allows us to more precisely and expressively characterize their behavior. We use this procedure to answ

Chihuang Liu, Joseph JaJa

Generating confidence calibrated outputs is of utmost importance for the applications of deep neural networks in safety-critical decision-making systems. The output of a neural network is a probability distribution where the scores are estimated confidences of the input belonging to the corresponding classes, and hence they represent a complete estimate of t

Matthew Jagielski, Giorgio Severi, Niklas Pousette Harger, Alina Oprea

Machine learning systems are deployed in critical settings, but they might fail in unexpected ways, impacting the accuracy of their predictions. Poisoning attacks against machine learning induce adversarial modification of data used by a machine learning algorithm to selectively change its output when it is deployed. In this work, we introduce a novel data p

Bruno Le Floch

Starting with a gentle approach to the AGT correspondence from its 6d origin, these notes provide a wide (albeit shallow) survey of the literature on numerous extensions of the correspondence up to early 2020. This is an extended writeup of the lectures given at the Winter School YRISW 2020, to appear in a special issue of JPhysA. Class S is a wide class of

Jing Yang, Jen-Tsung Hsiang, Andrew N. Jordan, B. L. Hu

In this paper, we show that a nonequilibrium steady state (NESS) exists at late times in open quantum systems with weak nonlinearity by following its nonequilibrium dynamics with a perturbative analysis. Here we consider an oscillator chain containing three-types of anharmonicity in the Fermi-Pasta-Ulam-Tsingou (FPUT) model: cubic $α$- and quartic $β$-type n

Emina Soljanin

Quantum information science is an exciting, wide, rapidly progressing, cross-disciplinary field, and that very nature makes it both attractive and hard to enter. In this primer, we first provide answers to the three essential questions that any newcomer needs to know: How is quantum information represented? How is quantum information processed? How is classi

David Jaz Myers

Every Grothendieck fibration gives rise to a vertical/cartesian orthogonal factorization system on its domain. We define a cartesian factorization system to be an orthogonal factorization in which the left class satisfies 2-of-3 and is closed under pullback along the right class. We endeavor to show that this definition abstracts crucial features of the vert

Howard S. Cohl, Roberto S. Costas-Santos, Linus Ge

In this survey paper, we exhaustively explore the terminating basic hypergeometric representations of the Askey-Wilson polynomials and the corresponding terminating basic hypergeometric transformations that these polynomials satisfy. From the terminating basic hypergeometric representations of these polynomials, and due to symmetry in their free parameters,

Ismael Mireles, Avi Shporer, Nolan Grieves, George Zhou

We report the discovery of TOI 694 b and TIC 220568520 b, two low-mass stellar companions in eccentric orbits around metal-rich Sun-like stars, first detected by the Transiting Exoplanet Survey Satellite (TESS). TOI 694 b has an orbital period of 48.05131$\pm$0.00019 days and eccentricity of 0.51946$\pm$0.00081, and we derive a mass of 89.0$\pm$5.3 $M_J$ (0.

J. Bayron Orjuela-Quintana, Miguel Alvarez, Cesar A. Valenzuela-Toledo, Yeinzon Rodriguez

In the context of the dark energy scenario, the Einstein Yang-Mills Higgs model in the SO(3) representation was studied for the first time by M. Rinaldi (see JCAP 1510, 023 (2015)) in a homogeneous and isotropic spacetime. We revisit this model, finding in particular that the interaction between the Higgs field and the gauge fields generates contributions to

Pavel Osinenko, Patrick Schmidt, Stefan Streif

This work has the goal of briefly surveying some key stabilization techniques for general nonlinear systems, for which, as it is well known, a smooth control Lyapunov function may fail to exist. A general overview of the situation with smooth and nonsmooth stabilization is provided, followed by a concise summary of basic tools and techniques, including gener

Di Wang, David M Kahn, Jan Hoffmann

This article presents a type-based analysis for deriving upper bounds on the expected execution cost of probabilistic programs. The analysis is naturally compositional, parametric in the cost model, and supports higher order functions and inductive data types. The derived bounds are multivariate polynomials that are functions of data structures. Bound infere

Ryan Alweiss, Yang P. Liu, Mehtaab Sawhney

We study discrepancy minimization for vectors in $\mathbb{R}^n$ under various settings. The main result is the analysis of a new simple random process in multiple dimensions through a comparison argument. As corollaries, we obtain bounds which are tight up to logarithmic factors for several problems in online vector balancing posed by Bansal, Jiang, Singla,

Yimeng Wang, G. William Burg, Biao Lian, Kenji Watanabe

Theoretical calculations show that twisted double bilayer graphene (TDBG) under a transverse electric field develops a valley Chern number 2 at charge neutrality. Using thermodynamic and thermal activation measurements we report the experimental observation of a universal closing of the charge neutrality gap in the Hofstadter spectrum of TDBG at 1/2 magnetic

Hang Qiu, Krishna Chintalapudi, Ramesh Govindan

Today, ground-truth generation uses data sets annotated by cloud-based annotation services. These services rely on human annotation, which can be prohibitively expensive. In this paper, we consider the problem of hybrid human-machine labeling, which trains a classifier to accurately auto-label part of the data set. However, training the classifier can be exp

Laise Dias, Diogo Diniz, Alex Ramos

In this paper we classify, up to isomorphism, the superinvolutions on algebras of upper block-triangular matrices over an algebraically closed field of characteristic different from $2$.

Ying Mao, Susiyan Jiang, Daniel Nametz, Yuxin Lin

The widely spread CoronaVirus Disease (COVID)-19 is one of the worst infectious disease outbreaks in history and has become an emergency of primary international concern. As the pandemic evolves, academic communities have been actively involved in various capacities, including accurate epidemic estimation, fast clinical diagnosis, policy effectiveness evalua

Bailey Winstanley, Henning Schomerus, Alessandro Principi

We study gated field effect transistors (FETs) with an eccentric Corbino-disk geometry, such that the drain spans its circumference while the off-center inner ring acts as a source. An AC THz potential difference is applied between source and gate while a static source-drain voltage, rectified by the nonlinearities of FET electrons, is measured. When a magne

Tamara Kucherenko, Anthony Quas, Christian Wolf

Let $ϕ:X\to \mathbb R$ be a continuous potential associated with a symbolic dynamical system $T:X\to X$ over a finite alphabet. Introducing a parameter $β>0$ (interpreted as the inverse temperature) we study the regularity of the pressure function $β\mapsto P_{\rm top}(βϕ)$ on an interval $[α,\infty)$ with $α>0$. We say that $ϕ$ has a phase transition at $β_

Alexey Sharapov, Evgeny Skvortsov

We give a complete classification of dynamical invariants in $3d$ and $4d$ Higher Spin Gravity models, with some comments on arbitrary $d$. These include holographic correlation functions, interaction vertices, on-shell actions, conserved currents, surface charges, and some others. Surprisingly, there are a good many conserved $p$-form currents with various

Henry-Louis de Kergorlay, Desmond John Higham

Anchor-based techniques reduce the computational complexity of spectral clustering algorithms. Although empirical tests have shown promising results, there is currently a lack of theoretical support for the anchoring approach. We define a specific anchor-based algorithm and show that it is amenable to rigorous analysis, as well as being effective in practice

Micha Berkooz, Vladimir Narovlansky, Himanshu Raj

We solve for the exact energy spectrum, 2-point and 4-point functions of the complex SYK model, in the double scaling limit at all energy scales. This model has a $U(1)$ global symmetry. The analysis shows how to incorporate a chemical potential in the chord diagram picture, and we present results for the various observables also at a given fixed charge sect

Alexis Conneau, Alexei Baevski, Ronan Collobert, Abdelrahman Mohamed

This paper presents XLSR which learns cross-lingual speech representations by pretraining a single model from the raw waveform of speech in multiple languages. We build on wav2vec 2.0 which is trained by solving a contrastive task over masked latent speech representations and jointly learns a quantization of the latents shared across languages. The resulting

David Stutz, Nandhini Chandramoorthy, Matthias Hein, Bernt Schiele

Deep neural network (DNN) accelerators received considerable attention in past years due to saved energy compared to mainstream hardware. Low-voltage operation of DNN accelerators allows to further reduce energy consumption significantly, however, causes bit-level failures in the memory storing the quantized DNN weights. In this paper, we show that a combina

Jonathan Stern, Claude-André Faucher-Giguère, Drummond Fielding, Eliot Quataert

We use the FIRE-2 cosmological simulations to study the formation of a quasi-static, virial-temperature gas phase in the circumgalactic medium (CGM) at redshifts 0<z<5, and how the formation of this virialized phase affects the evolution of galactic discs. We demonstrate that when the halo mass crosses ~10^12 M_sun, the cooling time of shocked gas in the inn

Takaaki Koike, Marius Hofert

We compare measures of concordance that arise as Pearson&#39;s linear correlation coefficient between two random variables transformed so that they follow the so-called concordance-inducing distributions. The class of such transformed rank correlations includes Spearman&#39;s rho, Blomqvist&#39;s beta and van der Waerden&#39;s coefficient. When only the stan

A. Ramachandran, G. R. Wilbur, S. O&#39;Neal, D. G. Deppe

We demonstrate full suppression of dephasing tied to deformation potential coupling of confined electrons to longitunidal acoustic (LA) phonons in optical control experiments on large semiconductor quantum dots (QDs) with emission compatible with the low-dispersion telecommunications band at 1.3~$μ$m. By exploiting the sensitivity of the electron-phonon spec

Adina V. Crişan, Ion V. Vancea

In this paper, we study the dynamics of the charged particle interacting with the non-null electromagnetic knot wave background. We analyse the classical system in the Hamilton-Jacobi formalism and find the action, the linear momentum and the trajectory of the particle. Also, we calculate the effective mass and the emitted radiation along the knot wave. Next

Parveen Kumar, Alessandro Romito, Kyrylo Snizhko

We study the Quantum Zeno Effect (QZE) induced by continuous partial measurement in the presence of short-correlated noise in the system Hamiltonian. We study the survival probability and the onset of the QZE as a function of the measurement strength, and find that, depending on the noise parameters, the quantum Zeno effect can be enhanced or suppressed by t

Xiaobo Lu, Biao Lian, Gaurav Chaudhary, Benjamin A. Piot

Moiré superlattices in two-dimensional (2D) van der Waals (vdW) heterostructures provide 20 an efficient way to engineer electron band properties. The recent discovery of exotic quantum phases and their interplay in twisted bilayer graphene (tBLG) has built this moiré system one of the most renowned condensed matter platforms (1-10). So far the studies of tB

Stephen R. Kane, Margaret C. Turnbull, Benjamin J. Fulton, Lee J. Rosenthal

Uncovering the occurrence rate of terrestrial planets within the Habitable Zone (HZ) of their host stars has been a particular focus of exoplanetary science in recent years. The statistics of these occurrence rates have largely been derived from transiting planet discoveries, and have uncovered numerous HZ planets in compact systems around M dwarf host stars

Mark Gonzalez, Mark P. Hertzberg, Fabrizio Rompineve

We examine whether the Hubble tension, the mismatch between early and late measurements of $H_0$, can be alleviated by ultralight scalar fields in the early universe, and we assess its plausibility within UV physics. Since their energy density needs to rapidly redshift away, we explore decays to massless fields around the era of matter-radiation equality. We

S. Bhargava, P. A. Giles, A. K. Romer, T. Jeltema

There have been several reports of a detection of an unexplained excess of X-ray emission at $\simeq$ 3.5 keV in astrophysical systems. One interpretation of this excess is the decay of sterile neutrino dark matter. The most influential study to date analysed 73 clusters observed by the XMM-Newton satellite. We explore evidence for a $\simeq$ 3.5 keV excess

Aseem Paranjape

The non-linear cosmic web environment of dark matter haloes plays a major role in shaping their growth and evolution, and potentially also affects the galaxies that reside in them. We develop an analytical (halo model) formalism to describe the tidal field of anisotropic halo-centric density distributions, as characterised by the halo-centric tidal tensor $\

L. Bassini, E. Rasia, S. Borgani, G. L. Granato

We studied the star formation rate (SFR) in cosmological hydrodynamical simulations of galaxy (proto-)clusters in the redshift range $0<z<4$, comparing them to recent observational studies; we also investigated the effect of varying the parameters of the star formation model on galaxy properties such as SFR, star-formation efficiency, and gas fraction. We an

Darshan G. Joshi, Subir Sachdev

A previous work (Joshi et al., arXiv:1912.08822) found a deconfined critical point at non-zero doping in a $t$-$J$ model with all-to-all and random hopping and spin exchange, and argued for its relevance to the phenomenology of the cuprates. We extend this model to include all-to-all and random density-density interactions of mean-square strength $K$. In a f

Jian Wang, Luiz H. Santos

We study quantum phase transitions in graphene superlattices in external magnetic fields, where a framework is presented to classify multiflavor Dirac fermion critical points describing hopping tuned topological phase transitions of integer and fractional Hofstadter-Chern insulators. We argue and provide numerical support for the existence of transitions tha

Clarke J. Esmerian, Andrey V. Kravtsov, Zachary Hafen, Claude-Andre Faucher-Giguere

We examine the thermodynamic state and cooling of the low-$z$ Circum-Galactic Medium (CGM) in five FIRE-2 galaxy formation simulations of Milky Way-mass galaxies. We find that the CGM in these simulations is generally multiphase and dynamic, with a wide spectrum of largely nonlinear density perturbations sourced by the accretion of gas from the Inter-Galacti

Petar Simidzija, Mark Van Raamsdonk

We argue that given holographic CFT$_1$ in some state with a dual spacetime geometry M, and given some other holographic CFT$_2$, we can find states of CFT$_2$ whose dual geometries closely approximate arbitrarily large causal patches of M, provided that CFT$_1$ and CFT$_2$ can be non-trivially coupled at an interface. Our CFT$_2$ states are &#34;dressed up

Djuna Croon, Gilly Elor, Rebecca K. Leane, Samuel D. McDermott

New light particles produced in supernovae can lead to additional energy loss and a consequent deficit in neutrino production in conflict with the neutrinos observed from Supernova 1987A (SN1987A). Contrary to the majority of previous SN1987A studies, we examine the impact of $Z&#39;$ bosons, axions, and axion-like particles (ALPs) interacting with the muons

Angelo Carollo, Dario Cilluffo, Francesco Ciccarello

Giant atoms are a new paradigm of quantum optics going beyond the usual local coupling. Building on this, a new type of decoherence-free (DF) many-body Hamiltonians was shown in a broadband waveguide. Here, these are incorporated in a general framework (not relying on master equations) and contrasted to dispersive DF Hamiltonians with normal atoms: the two s

Iosif Bena, Anthony Houppe, Nicholas P. Warner

Microstate geometries in string theory replace the black-hole horizon with a smooth geometric &#34;cap&#34; at the horizon scale. In geometries constructed using superstratum technology, this cap has the somewhat surprising property that induces very large tidal deformations on infalling observers that are far away from it. We find that this large-distance a

Jonah Herzog-Arbeitman, Zhi-Da Song, Nicolas Regnault, B. Andrei Bernevig

The Hofstadter problem is the lattice analog of the quantum Hall effect and is the paradigmatic example of topology induced by an applied magnetic field. Conventionally, the Hofstadter problem involves adding $\sim 10^4$ T magnetic fields to a trivial band structure. In this work, we show that when a magnetic field is added to an initially topological band s

Tommy Ohlsson, Marcus Pernow, Erik Sönnerlind

We derive the threshold corrections in $\mathrm{SO}(10)$ grand unified models with the intermediate symmetry being flipped $\mathrm{SU}(5)\times\mathrm{U}(1)$ or $\mathrm{SU}(3)\times\mathrm{SU}(2)\times\mathrm{U}(1)\times\mathrm{U}(1)$, with the masses of the scalar fields set by the survival hypothesis. These models do not achieve gauge coupling unificatio

Ming Y. Lu, Melissa Zhao, Maha Shady, Jana Lipkova

Cancer of unknown primary (CUP) is an enigmatic group of diagnoses where the primary anatomical site of tumor origin cannot be determined. This poses a significant challenge since modern therapeutics such as chemotherapy regimen and immune checkpoint inhibitors are specific to the primary tumor. Recent work has focused on using genomics and transcriptomics f

Kota Saito, Yuuya Yoshida

By using the work of Frantzikinakis and Wierdl, we can see that for all $d\in\mathbb{N}$, $α\in(d,d+1)$, and integers $k\ge d+2$ and $r\ge1$, there exist infinitely many $n\in\mathbb{N}$ such that the sequence $(\lfloor{(n+rj)^α}\rfloor)_{j=0}^{k-1}$ is represented as $\lfloor{(n+rj)^α}\rfloor=p(j)$, $j=0,1,\ldots,k-1$, by using some polynomial $p(x)\in\math

Haipeng An, Maxim Pospelov, Josef Pradler, Adam Ritz

We provide updates to the limits on solar emission of dark photons, or more generally any light vector particle coupled to the electron vector current. The recent 2019 and 2020 electronic recoil data from XENON1T now provides more stringent constraints on these models than stellar energy loss in the sub-keV mass region. We also show that solar emission of da

Peiyuan Zhu, Alexandre Bouchard-Côté, Trevor Campbell

Completely random measures provide a principled approach to creating flexible unsupervised models, where the number of latent features is infinite and the number of features that influence the data grows with the size of the data set. Due to the infinity the latent features, posterior inference requires either marginalization---resulting in dependence struct

Kasra Alishahi, Milad Barzegar

One of the equivalent formulations of the Kadison-Singer problem which was resolved in 2013 by Marcus, Spielman and Srivastava, is the &#34;paving conjecture&#34;. Roughly speaking, the paving conjecture states that every positive semi-definite contraction with small diagonal entries can be &#34;paved&#34; by a small number of principal submatrices with smal

Masha Baryakhtar, Asher Berlin, Hongwan Liu, Neal Weiner

Light dark sectors in thermal contact with the Standard Model naturally produce the observed relic dark matter abundance and are the targets of a broad experimental search program. A key light dark sector model is the pseudo-Dirac fermion with a dark photon mediator. The dynamics of the fermionic excited states are often neglected. We consider scenarios in w

Benjamin Eysenbach, Swapnil Asawa, Shreyas Chaudhari, Sergey Levine

We propose a simple, practical, and intuitive approach for domain adaptation in reinforcement learning. Our approach stems from the idea that the agent&#39;s experience in the source domain should look similar to its experience in the target domain. Building off of a probabilistic view of RL, we formally show that we can achieve this goal by compensating for

Arturo Deza, Qianli Liao, Andrzej Banburski, Tomaso Poggio

The main success stories of deep learning, starting with ImageNet, depend on deep convolutional networks, which on certain tasks perform significantly better than traditional shallow classifiers, such as support vector machines, and also better than deep fully connected networks; but what is so special about deep convolutional networks? Recent results in app

Anastasis Kratsios, Behnoosh Zamanlooy

Most $L^p$-type universal approximation theorems guarantee that a given machine learning model class $\mathscr{F}\subseteq C(\mathbb{R}^d,\mathbb{R}^D)$ is dense in $L^p_μ(\mathbb{R}^d,\mathbb{R}^D)$ for any suitable finite Borel measure $μ$ on $\mathbb{R}^d$. Unfortunately, this means that the model&#39;s approximation quality can rapidly degenerate outside

Matthew O&#39;Shaughnessy, Gregory Canal, Marissa Connor, Mark Davenport

We develop a method for generating causal post-hoc explanations of black-box classifiers based on a learned low-dimensional representation of the data. The explanation is causal in the sense that changing learned latent factors produces a change in the classifier output statistics. To construct these explanations, we design a learning framework that leverage

Andrea Angiuli, Jean-Pierre Fouque, Mathieu Laurière

We present a Reinforcement Learning (RL) algorithm to solve infinite horizon asymptotic Mean Field Game (MFG) and Mean Field Control (MFC) problems. Our approach can be described as a unified two-timescale Mean Field Q-learning: The \emph{same} algorithm can learn either the MFG or the MFC solution by simply tuning the ratio of two learning parameters. The a

Frank Gurski, Dominique Komander, Carolin Rehs

An acyclic r-coloring of a directed graph G=(V,E) is a partition of the vertex set V into r acyclic sets. The dichromatic number of a directed graph G is the smallest r such that G allows an acyclic r-coloring. For symmetric digraphs the dichromatic number equals the well-known chromatic number of the underlying undirected graph. This allows us to carry over

Yongsoo Jho, Jong-Chul Park, Seong Chan Park, Po-Yan Tseng

The recently reported excess in XENON1T is explained by new leptonic forces, which are free from gauge anomalies. We focus on two scenarios with and without dark matter. In Scenario #1, the gauge boson of gauged lepton number U(1)$_{L_e-L_j}$, $j=μ$ or $τ$ provides non-standard interaction between solar neutrino and electron that enhances the number of elect

Graciela B. Gelmini, Volodymyr Takhistov, Edoardo Vitagliano

A simple extension of the Standard Model consists of a scalar field that can potentially constitute the dark matter (DM). Significant attention has been devoted to probing light $\mathcal{O}(\lesssim 10~\rm{eV})$ scalar DM, with a multitude of experimental proposals based on condensed matter systems as well as novel materials. However, the previously overloo

Bao-Ming Xu, Jian Zou, Zhan-Chun Tu

In order to investigate the role of initial quantum coherence in work probability distribution, it is necessary to explicitly consider a concrete measurement apparatus to record work rather than implicitly appealing to perform an energy measurement. In this paper, we consider a harmonic oscillator with coherent or squeezing state as measurement apparatus, an

Dumindu Tissera, Kasun Vithanage, Rukshan Wijesinghe, Kumara Kahatapitiya

Learning a particular task from a dataset, samples in which originate from diverse contexts, is challenging, and usually addressed by deepening or widening standard neural networks. As opposed to conventional network widening, multi-path architectures restrict the quadratic increment of complexity to a linear scale. However, existing multi-column/path networ

M. Michael Denner, J. L. Lado, Oded Zilberberg

The advent of topological phases of matter revealed a variety of observed boundary phenomena, such as chiral and helical modes found at the edges of two-dimensional (2D) topological insulators. Antichiral states in 2D semimetals, i.e., copropagating edge modes on opposite edges compensated by a counterpropagating bulk current, are also predicted, but, to dat

M Said, A Biehl, A Stathopoulos

Active mobility offers an array of physical, emotional, and social wellbeing benefits. However, with the proliferation of the sharing economy, new nonmotorized means of transport are entering the fold, complementing some existing mobility options while competing with others. The purpose of this research study is to investigate the adoption of three active tr

Adam Gleave, Michael Dennis, Shane Legg, Stuart Russell

For many tasks, the reward function is inaccessible to introspection or too complex to be specified procedurally, and must instead be learned from user data. Prior work has evaluated learned reward functions by evaluating policies optimized for the learned reward. However, this method cannot distinguish between the learned reward function failing to reflect

Thorsten Beckmann, Georg Oberdieck

Given an action of a finite group $G$ on the derived category of a smooth projective variety $X$ we relate the fixed loci of the induced $G$-action on moduli spaces of stable objects in $D^b(\mathrm{Coh}(X))$ with moduli spaces of stable objects in the equivariant category $D^b(\mathrm{Coh}(X))_G$. As an application we obtain a criterion for the equivariant

Vinicius M. Netto, Edgardo Brigatti, Caio Cacholas

Cities are different around the world, but does this fact have any relation to culture? The idea that urban form embodies idiosyncrasies related to cultural identities captures the imagination of many in urban studies, but it is an assumption yet to be carefully examined. Approaching spatial configurations in the built environment as a proxy of urban culture

Jakub K. Sowa, Emily A. Weiss, Tamar Seideman

Photochromic molecular structures constitute a unique platform for constructing molecular switches, sensors and memory devices. One of their most promising applications is as light-switchable electron acceptor or donor units. Here, we investigate a previously unexplored process that we postulate may occur in such systems: an ultrafast electron transfer trigg

Oluwasegun Adedugbe, Elhadj Benkhelifa, Anoud Bani-Hani

Semantic technologies are designed to facilitate context-awareness for web content, enabling machines to understand and process them. However, this has been faced with several challenges, such as disparate nature of existing solutions and lack of scalability in proportion to web scale. With a holistic perspective to web content semantic annotation, this pape

João S. Ferreira, Michele Filippone

We study the ballistic-to-diffusive transition induced by the weak breaking of integrability in a boundary-driven XXZ spin-chain. Studying the evolution of the spin current density $\mathcal J^s$ as a function of the system size $L$, we show that, accounting for boundary effects, the transition has a non-trivial universal behavior close to the XX limit. It i

Yamin Li, Jiancheng Yang, Yi Xu, Jingwei Xu

Follow-up serves an important role in the management of pulmonary nodules for lung cancer. Imaging diagnostic guidelines with expert consensus have been made to help radiologists make clinical decision for each patient. However, tumor growth is such a complicated process that it is difficult to stratify high-risk nodules from low-risk ones based on morpholog

Caglar Gulcehre, Ziyu Wang, Alexander Novikov, Tom Le Paine

Offline methods for reinforcement learning have a potential to help bridge the gap between reinforcement learning research and real-world applications. They make it possible to learn policies from offline datasets, thus overcoming concerns associated with online data collection in the real-world, including cost, safety, or ethical concerns. In this paper, we

Shuhao Jiao, Ron D. Frostig, Hernando Ombao

Many experiments record sequential trajectories where each trajectory consists of oscillations and fluctuations around zero. Such trajectories can be viewed as zero-mean functional data. When there are structural breaks (on the sequence of trajectories) in higher order moments, it is not always easy to spot these by mere visual inspection. Motivated by this

S. D. Campos

Based on the Pomeranchuk theorem, one constructs the $δ(s)$ parameter to measure the difference between experimental data for the particle-particle and particle-antiparticle total cross section at the same energy. The experimental data for the proton-proton and proton-antiproton total cross section were used to show that, at the same energy, this parameter t

Ekaterina Svikhnushina, Pearl Pu

As chatbots are becoming increasingly popular, we often wonder what users perceive as natural and socially accepted manners of interacting with them. Some researchers maintain that humans should avoid engaging in emotional conversations with chatbots, while others have started building empathetic chatting machines using the latest deep learning techniques. T

Eduardo de Rafael

I discuss the possibility of estimating the shift $δΔα(M_Z^2)$ on the running of the EM-coupling to the $M_Z$ scale, induced by the discrepancy $Δa_μ$ between two precise determinations of the hadronic vacuum polarization contribution to $g_μ-2$. It is shown that the size of $Δa_μ$ implies rigorous bounds on the $δΔα(M_Z^2)$-shift. Any extra contribution to

Grace Yoon, Christian L. Müller, Irina Gaynanova

Latent Gaussian copula models provide a powerful means to perform multi-view data integration since these models can seamlessly express dependencies between mixed variable types (binary, continuous, zero-inflated) via latent Gaussian correlations. The estimation of these latent correlations, however, comes at considerable computational cost, having prevented

Carmelo Cisto, Francesco Navarra

In this paper we introduce a new class of polyominoes, called closed paths, and we study the primality of their associated ideal. Inspired by an existing conjecture that characterizes the primality of a polyomino ideal by nonexistence of zig-zag walks, we classify all closed paths which do not contain zig-zag walks, and we give opportune toric representation

Benjamin Briggs, Lleonard Rubio y Degrassi

We show that the restricted Lie algebra structure on Hochschild cohomology is invariant under stable equivalences of Morita type between self-injective algebras. Thereby we obtain a number of positive characteristic stable invariants, such as the $p$-toral rank of $\mathrm{HH}^1(A,A)$. We also prove a more general result concerning Iwanaga-Gorenstein algebra

Zhi-Wei Sun

Let $p$ be any prime and let $a$ and $n$ be positive integers with $p\nmid n$. We show that $$\sum_{k=1}^{p^a-1}\frac{B_k}{(-n)^k}\equiv a(-1)^{n-1}D_{n-1}\pmod {p},$$ where $B_0,B_1,\ldots$ are the Bell numbers and $D_0,D_1,\ldots$ are the derangement numbers. This extends a result of Sun and Zagier published in 2011. Furthermore, we prove that $$(-x)^n\sum

Víctor Peña, Kaoru Irie

Stochastic volatility processes are used in multivariate time-series analysis to track time-varying patterns in covariance matrices. Uhlig extended and beta-Bartlett processes are especially convenient for analyzing high-dimensional time-series because they are conjugate with Wishart likelihoods. In this article, we show that Uhlig extended and beta-Bartlett

Weilin Cong, Rana Forsati, Mahmut Kandemir, Mehrdad Mahdavi

Sampling methods (e.g., node-wise, layer-wise, or subgraph) has become an indispensable strategy to speed up training large-scale Graph Neural Networks (GNNs). However, existing sampling methods are mostly based on the graph structural information and ignore the dynamicity of optimization, which leads to high variance in estimating the stochastic gradients.

Xiaobin Hu, Yanyang Yan, Wenqi Ren, Hongwei Li

Artifacts, blur and noise are the common distortions degrading MRI images during the acquisition process, and deep neural networks have been demonstrated to help in improving image quality. To well exploit global structural information and texture details, we propose a novel biomedical image enhancement network, named Feedback Graph Attention Convolutional N

Maximilian Buser, Claudius Hubig, Ulrich Schollwöck, Leticia Tarruell

Flux ladders constitute the minimal setup enabling a systematic understanding of the rich physics of interacting particles subjected simultaneously to strong magnetic fields and a lattice potential. In this paper, the ground-state phase diagram of a flux-ladder model is mapped out using extensive density-matrix renormalization-group simulations. The emphasis

Dengsheng Chen, Jun Li, Kai Xu

Element-wise activation functions play a critical role in deep neural networks via affecting the expressivity power and the learning dynamics. Learning-based activation functions have recently gained increasing attention and success. We propose a new perspective of learnable activation function through formulating them with element-wise attention mechanism.

Domonkos F. Vamossy

Armed with a decade of social media data, I explore the impact of investor emotions on earnings announcements. In particular, I test whether the emotional content of firm-specific messages posted on social media just prior to a firm&#39;s earnings announcement predicts its earnings and announcement returns. I find that investors are typically excited about f

Chris A. Flett, Alan D. Martin, Misha G. Ryskin, Thomas Teubner

The low $x$ behaviour of the gluon density $xg(x,μ^2)$ at scale $μ^2=2.4$ GeV$^2$ is determined using exclusive $J/ψ$ production data from HERA and LHCb within the framework of collinear factorisation at next-to-leading order (NLO). It is shown that in the interval $3\times 10^{-6} < x <10^{-3}$ the gluon distribution function grows as $xg(x,μ^2)\propto x^{-

Felix Kern, Martin Linck, Daniel Wolf, Nasim Alem

The reduced dimensionality in two-dimensional materials leads a wealth of unusual properties, which are currently explored for both fundamental and applied sciences. In order to study the crystal structure, edge states, the formation of defects and grain boundaries, or the impact of adsorbates, high resolution microscopy techniques are indispensible. Here we

Matteo Gugiatti, Matteo Biassoni, Marco Carminati, Oliviero Cremonesi

Silicon Drift Detectors, widely employed in high-resolution and high-rate X-ray applications, are considered here with interest also for electron detection. The accurate measurement of the tritium beta decay is the core of the TRISTAN (TRitium Investigation on STerile to Active Neutrino mixing) project. This work presents the characterization of a single-pix

Matteo Fontana, Massimo Tavoni, Simone Vantini

Understanding the dynamics and evolution of climate change and associated uncertainties is key for designing robust policy actions. Computer models are key tools in this scientific effort, which have now reached a high level of sophistication and complexity. Model auditing is needed in order to better understand their results, and to deal with the fact that

Jim Nilsson, Tomas Akenine-Möller

The use of the structural similarity index (SSIM) is widespread. For almost two decades, it has played a major role in image quality assessment in many different research disciplines. Clearly, its merits are indisputable in the research community. However, little deep scrutiny of this index has been performed. Contrary to popular belief, there are some inter